Details
| Original language | English |
|---|---|
| Title of host publication | 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) |
| Pages | 5966-5973 |
| Number of pages | 8 |
| ISBN (electronic) | 978-1-6654-9190-7 |
| Publication status | Published - 2023 |
Publication series
| Name | Key-title Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems |
|---|---|
| ISSN (Print) | 2153-0858 |
| ISSN (electronic) | 2153-0866 |
Abstract
Parallel robots (PRs) offer the potential for safe human-robot collaboration because of their low moving masses. Due to the in-parallel kinematic chains, the risk of contact in the form of collisions and clamping at a chain increases. Ensuring safety is investigated in this work through various contact reactions on a real planar PR. External forces are estimated based on proprioceptive information and a dynamics model, which allows contact detection. Retraction along the direction of the estimated line of action provides an instantaneous response to limit the occurring contact forces within the experiment to 70 N at a maximum velocity of 0.4 m/s. A reduction in the stiffness of a Cartesian impedance control is investigated as a further strategy. For clamping, a feedforward neural network (FNN) is trained and tested in different joint angle configurations to classify whether a collision or clamping occurs with an accuracy of 80%. A second FNN classifies the clamping kinematic chain to enable a subsequent kinematic projection of the clamping joint angle onto the rotational platform coordinates. In this way, a structure opening is performed in addition to the softer retraction movement. The reaction strategies are compared in real-world experiments at different velocities and controller stiffnesses to demonstrate their effectiveness. The results show that in all collision and clamping experiments the PR terminates the contact in less than 130 ms.
ASJC Scopus subject areas
- Computer Science(all)
- Software
- Engineering(all)
- Control and Systems Engineering
- Computer Science(all)
- Computer Vision and Pattern Recognition
- Computer Science(all)
- Computer Science Applications
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2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2023. p. 5966-5973 (Key-title Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Safe Collision and Clamping Reaction for Parallel Robots During Human-Robot Collaboration
AU - Mohammad, Aran
AU - Schappler, Moritz
AU - Habich, Tim-Lukas
AU - Ortmaier, Tobias
N1 - Funding Information: ACKNOWLEDGMENT The authors acknowledge the support by the German Research Foundation (DFG) under grant number 444769341.
PY - 2023
Y1 - 2023
N2 - Parallel robots (PRs) offer the potential for safe human-robot collaboration because of their low moving masses. Due to the in-parallel kinematic chains, the risk of contact in the form of collisions and clamping at a chain increases. Ensuring safety is investigated in this work through various contact reactions on a real planar PR. External forces are estimated based on proprioceptive information and a dynamics model, which allows contact detection. Retraction along the direction of the estimated line of action provides an instantaneous response to limit the occurring contact forces within the experiment to 70 N at a maximum velocity of 0.4 m/s. A reduction in the stiffness of a Cartesian impedance control is investigated as a further strategy. For clamping, a feedforward neural network (FNN) is trained and tested in different joint angle configurations to classify whether a collision or clamping occurs with an accuracy of 80%. A second FNN classifies the clamping kinematic chain to enable a subsequent kinematic projection of the clamping joint angle onto the rotational platform coordinates. In this way, a structure opening is performed in addition to the softer retraction movement. The reaction strategies are compared in real-world experiments at different velocities and controller stiffnesses to demonstrate their effectiveness. The results show that in all collision and clamping experiments the PR terminates the contact in less than 130 ms.
AB - Parallel robots (PRs) offer the potential for safe human-robot collaboration because of their low moving masses. Due to the in-parallel kinematic chains, the risk of contact in the form of collisions and clamping at a chain increases. Ensuring safety is investigated in this work through various contact reactions on a real planar PR. External forces are estimated based on proprioceptive information and a dynamics model, which allows contact detection. Retraction along the direction of the estimated line of action provides an instantaneous response to limit the occurring contact forces within the experiment to 70 N at a maximum velocity of 0.4 m/s. A reduction in the stiffness of a Cartesian impedance control is investigated as a further strategy. For clamping, a feedforward neural network (FNN) is trained and tested in different joint angle configurations to classify whether a collision or clamping occurs with an accuracy of 80%. A second FNN classifies the clamping kinematic chain to enable a subsequent kinematic projection of the clamping joint angle onto the rotational platform coordinates. In this way, a structure opening is performed in addition to the softer retraction movement. The reaction strategies are compared in real-world experiments at different velocities and controller stiffnesses to demonstrate their effectiveness. The results show that in all collision and clamping experiments the PR terminates the contact in less than 130 ms.
UR - http://www.scopus.com/inward/record.url?scp=85170507466&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2308.09656
DO - 10.48550/arXiv.2308.09656
M3 - Conference contribution
SN - 978-1-6654-9191-4
T3 - Key-title Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems
SP - 5966
EP - 5973
BT - 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
ER -